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All Journal International Journal of Electrical and Computer Engineering
Mohammed Mahdi
Jordan University of Science and Technology
Computer Science & IT Electrical & Electronics Engineering

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Computed tomography scans image processing for nasal symptoms severity prediction Amjad Nuseir; Hasan Albalas; Aya Nuseir; Maulla Alali; Firas Zoubi; Mahmoud Al-Ayyoub; Mohammed Mahdi; Ahmad Al Omari
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1488-1497

Abstract

This paper aims to use a new technique of computed tomography (CT) scan image processing to correlate the image analysis with sinonasal symptoms. A retrospective cross-sectional study is conducted by analyzing the digital records of 50 patients who attended the ear, nose and throat (ENT) clinics at King Abdullah University Hospital, Jordan. The coronal plane CT scans are analyzed using our developed software. The purposes of this software are to calculate the surface area of the nasal passage at three different levels visible on coronal plane CT scans: i) the head of the inferior turbinate, ii) the head of the middle turbinate, and iii) the tail of the inferior turbinate. We employ image processing techniques to correlate the narrowing of nasal surface area with sinonasal symptoms. As a consequence, obstruction in the first level is correlated significantly with the symptoms of nasal obstruction while the narrowing in the second level is related to frontal headache. No other significant correlations are found with nasal symptoms at the third level. In our study, we find that image processing techniques can be very useful to predict the severity of common nasal symptoms and they can be used to suggest treatment and to follow up on the case progression.
Co-Authors Ahmad Al Omari Amjad Nuseir Aya Nuseir Firas Zoubi Hasan Albalas Mahmoud Al-Ayyoub Maulla Alali